Significance of Sensor Location in Real-time Traffic State Estimation

Author:

Ahmed Afzal,Watling David,Ngoduy Dong

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference14 articles.

1. Real-Time Freeway Traffic State Estimation Based on Extended Kalman Filter: Adaptive Capabilities and Real Data Testing;Wang;Transportation Research Part A: Policy and Practice,2008

2. Real-Time Freeway Traffic State Estimation Based on Extended Kalman Filter: A General Approach [In English];Wang;Transportation Research Part B-Methodological,2005

3. Modeling and Real-Time Control of Traffic Flow on the Southern Part of Boulevard-Peripherique in Paris .1 Modeling. [In English];Papageorgiou;Transportation Research Part a-Policy and Practice,1990

4. Kernel Smoothing Method Applicable to the Dynamic Calibration of Traffic Flow Models;Ngoduy;Computer-Aided Civil and Infrastructure Engineering,2011

5. Applicable Filtering Framework for Online Multiclass Freeway Network Estimation. Physica A;Ngoduy;Statistical Mechanics and its Applications,2008

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2. Real-Time Dynamic Traffic Control Based on Traffic-State Estimation;Transportation Research Record: Journal of the Transportation Research Board;2019-04-04

3. Reliable sensor location for object positioning and surveillance via trilateration;Transportation Research Part B: Methodological;2018-11

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